Abstract
In the IoT (Internet of Things), a large volume of electric energy is consumed by a large number of devices and servers. In the FC (Fog Computing) model of the IoT, parts of application processes for sensor data are executed on fog nodes. In our previous studies, the TBFC (Tree-Based FC) model is proposed, where application processes are replicated and distributed to fog nodes structured in a tree. In the FTBFC (Flexible TBFC) model, operations for changing the tree structure are proposed. In this paper, a novel EAC (Energy-Aware Change tree) algorithm is proposed, by wich the tree structure and processes on fog nodes are changed to reduce the energy consumption. Here, a target node which consumes the largest energy in the tree is selected and the tree is changed by applying the TC (Tree Change) operations on the target node. In the evaluation, we show the total energy consumption of nodes in the EAC algorithm is about 60% smaller than the CC model.
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References
Dayarathna, M., Wen, Y., Fan, R.: Data center energy consumption modeling: a survey. IEEE Commun. Surv. Tutorials 18(1), 732–787 (2016)
Qian, L., Luo, Z., Du, Y., Guo, L.: Cloud computing: an overview. In: Jaatun, M.G., Zhao, G., Rong, C. (eds.) CloudCom 2009. LNCS, vol. 5931, pp. 626–631. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-10665-1_63
Rahmani, A.M., Liljeberg, P., Preden, J.-S., Jantsch, A.: Fog Computing in the Internet of Things, 1st edn., p. 172. Springer, Cham (2018)
Enokido, T., Aikebaier, A., Takizawa, M.: Process allocation algorithms for saving power consumption in peer-to-peer systems. IEEE Trans. Ind. Electron. 58(6), 2097–2105 (2011)
Enokido, T., Aikebaier, A., Takizawa, M.: A model for reducing power consumption in peer-to-peer systems. IEEE Syst. J. 4(2), 221–229 (2010)
Enokido, T., Aikebaier, A., Takizawa, M.: An extended simple power consumption model for selecting a server to perform computation type processes in digital ecosystems. IEEE Trans. Ind. Inf. 10(2), 1627–1636 (2014)
Enokido, T., Takizawa, M.: Integrated power consumption model for distributed systems. IEEE Trans. Ind. Electron. 60(2), 824–836 (2013)
Kataoka, H., Duolikun, D., Sawada, A., Enokido, T., Takizawa, M.: Energy-aware server selection algorithms in a scalable cluster. In: Proceedings of the 30th International Conference on Advanced Information Networking and Applications, pp. 565–572 (2016)
Kataoka, H., Nakamura, S., Duolikun, D., Enokido, T., Takizawa, M.: Multi-level power consumption model and energy-aware server selection algorithm. Int. J. Grid Utility Comput. 8(3), 201–210 (2017)
Duolikun, D., Enokido, T., Takizawa, M.: Energy-efficient dynamic clusters of servers. In: Proceedings of the 8th International Conference on Broadband and Wireless Computing, Communication and Applications, pp. 253–260 (2013)
Duolikun, D., Enokido, T., Takizawa, M.: Static and dynamic group migration algorithms of virtual machines to reduce energy consumption of a server cluster. In: Nguyen, N.T., Kowalczyk, R., Xhafa, F. (eds.) Transactions on Computational Collective Intelligence XXXIII. LNCS, vol. 11610, pp. 144–166. Springer, Heidelberg (2019). https://doi.org/10.1007/978-3-662-59540-4_8
Duolikun, D., Enokido, T., Takizawa, M.: Simple algorithms for selecting an energy-efficient server in a cluster of servers. Int. J. Commun. Netw. Distrib. Syst. 21(1), 1–25 (2018)
Duolikun, D., Enokido, T., Barolli, L., Takizawa, M.: A monotonically increasing (MI) algorithm to estimate energy consumption and execution time of processes on a server. In: Proceedings of the 24th International Conference on Network-Based Information Systems, pp. 1–12 (2021)
Duolikun, D., Nakamura, S., Enokido, T., Takizawa, M.: Energy-consumption evaluation of the tree-based fog computing (TBFC) model. In: Barolli, L. (ed.) BWCCA 2022. Lecture Notes in Networks and Systems, vol. 570, pp. 66–77. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-20029-8_7
Duolikun, D., Enokido, T., Barolli, L., Takizawa, M.: A flexible fog computing (FTBFC) model to reduce energy consumption of the IoT. In: Barolli, L. (ed.) EIDWT 2023. Lecture Notes on Data Engineering and Communications Technologies, vol. 161, pp. 256–262. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-26281-4_26
Duolikun, D., Enokido, T., Takizawa, M.: An energy-aware algorithm for changing tree structure and process migration in the flexible tree-based fog computing model. In: Barolli, L. (ed.) AINA 2023. Lecture Notes in Networks and Systems, vol. 654, pp. 268–278. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-28451-9_24
Mukae, K., Saito, T., Nakamura, S., Enokido, T., Takizawa, M.: Design and implementing of the dynamic tree-based fog computing (DTBFC) model to realize the energy-efficient IoT. In: Barolli, L., Natwichai, J., Enokido, T. (eds.) EIDWT 2021. LNDECT, vol. 65, pp. 71–81. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-70639-5_7
Oma, R., Nakamura, S., Duolikun, D., Enokido, T., Takizawa, M.: An energy-efficient model for fog computing in the Internet of Things (IoT). Internet Things 1–2, 14–26 (2018)
Oma, R., Nakamura, S., Enokido, T., Takizawa, M.: A tree-based model of energy-efficient fog computing systems in IoT. In: Barolli, L., Javaid, N., Ikeda, M., Takizawa, M. (eds.) CISIS 2018. AISC, vol. 772, pp. 991–1001. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-93659-8_92
Oma, R., Nakamura, S., Duolikun, D., Enokido, T., Takizawa, M.: Evaluation of an energy-efficient tree-based model of fog computing. In: Barolli, L., Kryvinska, N., Enokido, T., Takizawa, M. (eds.) NBiS 2018. LNDECT, vol. 22, pp. 99–109. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-98530-5_9
Oma, R., Nakamura, S., Duolikun, D., Enokido, T., Takizawa, M.: A fault-tolerant tree-based fog computing model. Int. J. Web Grid Serv. 15(3), 219–239 (2019)
Oma, R., Nakamura, S., Duolikun, D., Enokido, T., Takizawa, M.: Energy-efficient recovery algorithm in the fault-tolerant tree-based fog computing (FTBFC) model. In: Barolli, L., Takizawa, M., Xhafa, F., Enokido, T. (eds.) AINA 2019. AISC, vol. 926, pp. 132–143. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-15032-7_11
Oma, R., Nakamura, S., Enokido, T., Takizawa, M.: A dynamic tree-based fog computing (DTBFC) model for the energy-efficient IoT. In: Barolli, L., Okada, Y., Amato, F. (eds.) EIDWT 2020. LNDECT, vol. 47, pp. 24–34. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-39746-3_4
Guo, Y., Saito, T., Oma, R., Nakamura, S., Enokido, T., Takizawa, M.: Distributed approach to fog computing with auction method. In: Barolli, L., Amato, F., Moscato, F., Enokido, T., Takizawa, M. (eds.) AINA 2020. AISC, vol. 1151, pp. 268–275. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-44041-1_25
Raspberry pi 3 model b (2016). https://www.raspberrypi.org/products/raspberry-pi-3-model-b
Acknowledgment
This work is supported by Japan Society for the Promotion of Science (JSPS) KAKENHI Grant Number 22K12018.
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Duolikun, D., Enokido, T., Takizawa, M. (2023). Evaluation of the FTBFC Model for Energy-Efficient IoT. In: Barolli, L. (eds) Advances in Networked-based Information Systems. NBiS 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 183. Springer, Cham. https://doi.org/10.1007/978-3-031-40978-3_7
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